Grant Thornton
Turning 200+ Leases Into Actionable Intelligence
How AI agents automated aircraft utilization tracking for a global professional services firm.
The Challenge
Grant Thornton's aviation practice advises lessors managing billions in aircraft assets. Each month, lessors receive utilization reports from airlines - PDFs filled with flight hours, cycles, maintenance data, and financial calculations.
The problem: extracting this data manually was eating 40+ hours per week. Analysts were copying numbers from PDFs into spreadsheets, cross-referencing lease terms, and flagging discrepancies. It was slow, error-prone, and soul-crushing work.
They needed a solution that could read utilization reports in any format, extract flight hours, cycles, and maintenance reserves, cross-reference against lease agreements, and flag anomalies for human review.
The Solution
We built two AI agents that work together to automate the entire extraction and analysis workflow:
Agent Zeus - The Extractor
Reads PDF utilization reports regardless of format. Extracts 50+ data points per document. Handles handwritten annotations and scanned documents. Learns from corrections to improve over time.
Agent Hercules - The Analyzer
Cross-references extracted data against lease terms. Calculates expected vs. actual utilization. Flags discrepancies for analyst review. Generates standardized output for downstream systems.
The Results
"What used to take our analysts an entire week now happens overnight. The accuracy improvements alone justified the investment."